Marine traffic

Table S1. Summary of 2019 marine traffic within the lower Kitimat Fjord System, as reported by archival AIS data.
Speed (kn)
Length (m)
Beam (m)
Draft (m)
Type VIDs Transits mean sd max mean sd min max mean sd min max mean sd min max
Cargo ship 54 157 12.7 1.7 17.1 159 53 26 200 26 8 7 33 8.2 2.6 3.0 11.0
Cargo ship:DG,HS,MP(X) 1 2 11.9 0.7 13.7 67 0 67 67 13 0 13 13 5.0 0.0 5.0 5.0
Diving op. 1 4 7.8 0.7 10.0 10 0 10 10 4 0 4 4 0.5 0.0 0.5 0.5
Dredging or underwater op. 3 36 9.7 2.4 15.0 63 34 35 119 14 6 9 22 4.4 0.5 4.0 5.0
Fishing 308 829 8.4 3.2 32.2 20 9 6 100 6 2 1 20 1.5 1.2 0.4 10.0
HSC 3 8 13.0 8.1 28.6 25 13 7 35 7 3 3 10 2.6 1.7 0.4 4.0
Law enforcement 3 3 9.7 1.5 12.6 42 16 26 68 8 3 6 14 2.8 0.8 2.0 4.0
Local ship 2 10 12.4 6.5 26.5 13 4 10 18 4 0 4 5 0.6 0.2 0.5 0.9
Military op. 1 4 9.1 2.4 15.0 33 0 33 33 8 0 8 8 3.0 0.0 3.0 3.0
Other 22 78 8.6 2.4 24.9 37 22 6 76 9 5 2 20 3.3 1.9 0.3 6.0
Passenger ship 58 803 15.1 5.7 35.6 108 75 11 301 18 10 3 36 4.0 2.2 0.6 8.0
Passenger ship:DG,HS,MP(Y) 1 2 11.1 0.4 11.8 64 0 64 64 12 0 12 12 3.0 0.0 3.0 3.0
Pilot 2 6 19.9 3.1 25.8 19 1 17 20 4 1 3 5 1.0 0.0 1.0 1.0
Pleasure Craft 275 1213 8.2 3.7 37.5 20 16 7 154 6 3 1 18 1.1 1.0 0.4 9.0
Port tender 1 2 7.4 1.1 8.8 26 0 26 26 8 0 8 8 8.0 0.0 8.0 8.0
Sailing 117 426 6.0 1.3 12.6 14 4 8 35 4 1 1 8 0.7 0.3 0.4 3.0
Search/rescue 14 193 10.3 4.0 39.2 52 15 7 83 11 3 2 17 4.6 1.0 0.4 6.0
Tanker 2 7 12.1 0.8 13.9 141 5 134 145 24 0 24 24 8.7 0.5 8.0 9.0
Towing 36 356 7.0 1.7 21.7 27 21 6 162 8 3 4 24 3.3 1.8 0.3 7.0
Towing(200/25) 42 382 8.8 1.6 13.7 32 6 12 41 10 2 2 12 4.7 1.4 1.7 7.0
Tug 62 873 7.4 1.8 13.9 27 28 11 178 8 3 4 22 3.1 1.8 0.6 6.0

 

 

Table S2. AIS traffic in 2019, restricted to prime fin whale habitat in Squally Channel, including Lewis Passage and north Campania Sound (W 129.4519 - 129.26239, N 53.069 - 53.3218)
Speed (kn)
Length (m)
Beam (m)
Draft (m)
Vessel type IDs Transits Transits/day mean sd max mean sd min max mean sd min max mean sd min max
Cargo > 180m 4 4 0.01 12.4 1.6 14.6 187 8 180 200 31 1 30 32 10.2 0.9 9.0 11
Fishing < 60m 30 75 0.21 8.2 4.3 32.2 17 6 10 37 6 2 4 12 1.2 0.9 0.5 6
Other < 40m 6 20 0.05 8.8 4.9 31.5 26 8 7 40 6 2 2 9 2.0 1.7 0.4 5
Other > 100m 5 9 0.02 10.4 2.0 13.5 157 19 134 178 18 8 4 29 6.6 1.6 4.0 9
Other > 40m 13 59 0.16 9.5 2.4 15.0 55 14 42 98 13 3 9 22 3.9 1.4 2.0 6
Passenger > 180m 5 19 0.05 18.1 2.5 22.0 270 39 197 301 33 1 28 34 7.8 0.4 7.0 8
Pleasurecraft < 40m 70 142 0.39 7.4 3.6 34.4 15 5 7 28 5 1 2 7 0.7 0.2 0.4 2
Sailing 17 35 0.10 5.6 1.4 9.0 15 5 8 32 4 2 2 8 0.8 0.4 0.4 3
Towing < 50m 14 40 0.11 9.2 1.4 11.8 34 4 26 41 10 2 6 12 5.2 1.2 1.7 6
Tug < 50m 17 74 0.20 7.1 1.9 11.2 23 9 12 41 8 2 4 12 3.2 1.7 0.6 6

 

Figure S1. Length distributions of the ten vessel classes used to summarize marine traffic in 2019.

Figure S1. Length distributions of the ten vessel classes used to summarize marine traffic in 2019.

 

Figure S2. Speed distributions, in knots, of the ten vessel classes used to summarize marine traffic in 2019.

Figure S2. Speed distributions, in knots, of the ten vessel classes used to summarize marine traffic in 2019.

 

Figure S3. Seasonal patterns in the speed (knots) of marine traffic, grouped iinto the 10 vessel classes used in this study.

Figure S3. Seasonal patterns in the speed (knots) of marine traffic, grouped iinto the 10 vessel classes used in this study.

 

Figure S4.Seasonal patterns in the length (meters) of marine traffic, grouped iinto the 10 vessel classes used in this study.

Figure S4.Seasonal patterns in the length (meters) of marine traffic, grouped iinto the 10 vessel classes used in this study.

 

Table S3. Trends (historical and predicted) in AIS traffic, 2014 - 2030. Kilometers transited in 2014 - 2019 are observations, while the 2030 numbers are predicted based on linear models. The “scale factor” is the multiplier used, based on those models, to estimate 2030 transits based on 2019 data. “Prop. change” is the proportional rate of annual change in total transits (e.g., the “2019” proportion column shows the rate of change as a proportion of 2019 transits). The p-value refers to the linear model for each vessel class.
Kilometers transited
Prop. change
Vessel class 2014 2015 2018 2019 2030 Scale factor 2019 2030 p-value
Cargo > 180m 0 0 0 9444 16943 1.79 0.15 0.08 0.30
Fishing < 60m 17165 16377 31949 45784 86437 1.89 0.12 0.06 0.05
Other < 40m 62201 87269 57399 18723 0 0.00 -0.48 -0.24 0.24
Other > 100m 25213 19011 27281 26166 33552 1.28 0.03 0.03 0.44
Other > 40m 27391 9943 23408 29184 37725 1.29 0.05 0.04 0.60
Passenger > 180m 6212 5489 10403 6168 11554 1.87 0.07 0.04 0.55
Pleasurecraft < 40m 0 0 56 51215 91952 1.80 0.15 0.08 0.30
Sailing 357 1553 12538 20934 50795 2.43 0.19 0.08 0.02
Towing < 50m 35311 15299 39409 42838 67175 1.57 0.08 0.05 0.38
Tug < 50m 30971 44685 46344 43301 61901 1.43 0.05 0.03 0.33

 

Figure S5. Changes in total transit kilometers for the 10 vessel classes in our study, 2014 - 2019.

Figure S5. Changes in total transit kilometers for the 10 vessel classes in our study, 2014 - 2019.

 

Table S4. Dimensions of the LNG Canada fleet, adapted from TERMPOL (2015). Note that in our analyses, we reduced the max Shell length to 298m, and the beam was adjusted according to the original length:beam ratio.

 

 

Methods details

Line-transect surveys

Table S5. Effort and sighting details from line-trasect surveys within the Kitimat Fjord Surveys, 2013 - 2015. For each species, “total” counts include all detections while on systematic effort, while “valid” counts include detections with valid detection-distance estimates.
Effort
Fin whales
Humpback whales
Year segments km total valid total valid
2013 143 712.5204 8 6 68 38
2014 168 800.5337 18 17 134 130
2015 402 2083.1364 19 19 253 251

 

Figure S6. (a) Design-based line-transect survey effort throughout the central Gitga’at waters of the Kitimat Fjord System (each dot is the center of a 5-km segment of systematic effort), yielding detections of (b) fin whales and (c) humpback whales. Detection dot size reflects group size

 

Table S6. Best-fitting models of the detection functions for fin whales and humpback whales, based upon 2013-2015 line-transect surveys.
Species Model Key function Formula C-vM p-value \(\hat{P_a}\) se(\(\hat{P_a}\)) \(\Delta\)AIC
1 Fin whale 1 Half-normal ~1 0.8405095 0.5500191 0.0742873 0.0000000
3 2 Half-normal ~1 + factor(year) 0.7815848 0.5231299 0.0742940 0.3047398
2 3 Half-normal ~1 + bft 0.8250065 0.5465154 0.0793721 1.5958236
31 Humpback whale 1 Half-normal ~1 + factor(year) 0.9652267 0.5204825 0.0213641 0.0000000
21 2 Half-normal ~1 + bft 0.9637787 0.5296131 0.0215150 9.0061244
11 3 Half-normal ~1 0.9430440 0.5364511 0.0213979 15.9211900

 

Figure S7. Best-fitting detection function models superimposed upon histograms of detection distances for each species.

Figure S7. Best-fitting detection function models superimposed upon histograms of detection distances for each species.

 

Figure S8. Bathymetric characteristics of the study area, as summarized for the square-kilometer grid used in density surface modeling.

 

Humpback whale UAS analysis

Table S7. Humpback whale morphometrics (n=13 individuals) measured by UAS in Gitga’at waters in 2019.
Measurements
Body length (m)
Fluke width (m)
Whale ID Total Score 1 Score 2 Mean SD Score 1 Score 2 Mean SD Score 1 Score 2
20190611 1A 5 3 2 11.19 0.27 11.09 11.34 3.52 0.11 3.49 3.60
20190829 1A 1 1 0 11.08 11.08 3.58 3.58
20190829 1B 4 1 3 10.92 0.33 11.10 10.86 3.76 0.15 3.92 3.69
20190905 1A 10 4 6 11.17 0.62 11.08 11.22 3.93 0.22 3.89 3.96
20190905 1B 2 1 1 11.39 0.20 11.25 11.53 4.21 0.08 4.27 4.15
20190905 2A 4 2 2 14.45 0.29 14.68 14.22 4.38 0.11 4.44 4.33
20190905 2B 3 2 1 13.26 0.28 13.42 12.94 4.21 0.10 4.17 4.28
20190907 1A 3 1 2 11.67 0.22 11.90 11.55 3.98 0.03 3.96 3.99
20190908 1A 1 1 0 10.97 10.97 3.53 3.53
20190909 1A 3 2 1 13.34 0.11 13.34 13.32 4.44 0.12 4.51 4.30
20190909 1B 5 2 3 10.41 0.35 10.77 10.17 3.59 0.10 3.67 3.53
20190910 1A 1 0 1 12.36 12.36 4.01 4.01
20190911 1A 8 3 5 10.94 0.48 10.93 10.95 3.54 0.10 3.54 3.54
20190911 1B 1 0 1 11.08 11.08 3.96 3.96
20191004 1A 9 7 2 13.64 0.21 13.68 13.49 4.13 0.06 4.13 4.09
Table S8. Summary of UAS flights used to estimate humpback whale swimming speed. Multiple follows of the same group were averaged together before calculating speed.
Duration (sec)
Distance (km)
Date File Follows Mean Total Mean Total Speed (m/s)
2019-06-06 20190606_DJI_0079 1 31.00 31 0.03 0.03 0.836
2019-08-28 20190828_DJI_0552_Group1 1 43.00 43 0.00 0.00 0.039
2019-08-29 20190829_DJI_0556_Group1 3 50.67 152 0.03 0.08 0.501
2019-09-03 20190903_DJI_0564_Group1 1 68.00 68 0.07 0.07 1.017
2019-09-05 20190905_DJI_0575_Group1 1 71.00 71 0.01 0.01 0.210
2019-09-05 20190905_DJI_0578_Group1 2 84.50 169 0.04 0.07 0.430
2019-09-05 20190905_DJI_0582_Group2 1 42.00 42 0.03 0.03 0.768
2019-09-05 20190905_DJI_0585_Group2 2 50.50 101 0.02 0.04 0.353
2019-09-07 20190907_DJI_0591_Group3 2 48.00 96 0.03 0.06 0.675
2019-09-07 20190907_DJI_0593_Group3 2 98.00 196 0.07 0.15 0.754
2019-09-08 20190908_DJI_0597_Group1and2 1 41.00 41 0.02 0.02 0.580
2019-09-08 20190908_DJI_0600_Group3 1 64.00 64 0.03 0.03 0.525
2019-09-11 20190911_DJI_0620_Group2 2 46.50 93 0.04 0.08 0.812
2019-10-04 20191004_DJI_0624_Group1 1 78.00 78 0.05 0.05 0.663

Fin whale dive tag analysis

Figure S9. Raw time- and depth-distributions of depth sensor readings for each of the 7 SPLASH-10 tag deployments.

Figure S9. Raw time- and depth-distributions of depth sensor readings for each of the 7 SPLASH-10 tag deployments.

 

Figure S10. Time distribution (hour of day, color-coded by daytime/nighttime) of depth samples from SPLASH10 tags, displayed for each deployment separately.

Figure S10. Time distribution (hour of day, color-coded by daytime/nighttime) of depth samples from SPLASH10 tags, displayed for each deployment separately.

 

Table S9. Summary of SPLASH10 depth data used in fin whale depth distribution analysis.
Deployment ID
Deployment period
Depth sample size
This study Nichol et al. (2018) Start Stop Hours Hours valid Total Day Night Prop. valid
1 132219-132219 2013-08-19 23:00:00 2013-08-24 20:58:45 117.97917 8.00000 384 336 48 0.07
2 132220-132220 2013-08-18 18:47:30 2013-08-28 19:57:30 241.16667 26.18750 1257 837 420 0.11
3 137684-137684 2014-08-16 00:15:00 2014-08-16 23:57:30 23.70833 23.72917 1139 835 304 1.00
4 137685-137685 2014-08-20 18:22:30 2014-09-04 21:58:45 363.60417 45.62500 2190 1720 470 0.13
5 137686-137686 2014-08-23 16:30:00 2014-09-02 13:57:30 237.45833 18.47917 887 792 95 0.08
6 142546-142546 2014-09-08 19:00:00 2014-09-28 23:58:45 484.97917 82.00000 3936 2468 1468 0.17
7 142547-142547 2014-09-14 00:00:00 2014-09-14 10:58:45 10.97917 4.00000 192 96 96 0.36

 

Figure S11. Daytime (left) and nighttime (right) depth distribution curves, representing the proportion of time spent above a given depth, for six SPLASH-10 deployments on fin whales (colored lines).

Figure S11. Daytime (left) and nighttime (right) depth distribution curves, representing the proportion of time spent above a given depth, for six SPLASH-10 deployments on fin whales (colored lines).

 

Collision & mortality analysis

 

Figure S12. Probabilities of collision (left) and mortality (right) as a function of ship speed (>180m length), adapted from Gende et al. (2011) and Kelley et al. (2020), respectively.

Figure S12. Probabilities of collision (left) and mortality (right) as a function of ship speed (>180m length), adapted from Gende et al. (2011) and Kelley et al. (2020), respectively.

 

Potential Biological Removal

Fin whales – Canadian Pacific stock (Wright et al. 2022):

pbr(N = 2893, CV = 0.15) %>% cbind
##         .       
## PBR     15.91859
## Nmin    795.9295
## Rmax    0.08    
## Fr      0.5     
## Nmedian 2916.097

Fin whales – North Coast Sector (Wright et al. 2022):

pbr(N = 161, CV = 0.50)  %>% cbind
##         .       
## PBR     1.278049
## Nmin    63.90245
## Rmax    0.08    
## Fr      0.5     
## Nmedian 162.9447

Fin whales – coastal (Queen Charlotte, Hecate Strait) (Nichol et al 2017):

pbr(N = 405, CV = 0.6)  %>% cbind
##         .       
## PBR     2.799279
## Nmin    139.9639
## Rmax    0.08    
## Fr      0.5     
## Nmedian 410.8592

Humpback whales – Canadian Pacific stock (Wright et al. 2022):

pbr(N = 7030, CV = 0.1)  %>% cbind
##         .       
## PBR     34.81307
## Nmin    1740.654
## Rmax    0.08    
## Fr      0.5     
## Nmedian 7000.519

Humpback whales – North Coast sector (Wright et al. 2022):

pbr(N = 1816, CV = 0.13)  %>% cbind
##         .       
## PBR     10.51564
## Nmin    525.7821
## Rmax    0.08    
## Fr      0.5     
## Nmedian 1844.58

Results details

Vessel traffic

Figure S13. Distribution of 2019 marine traffic parsed by waterway and time of day.

Figure S13. Distribution of 2019 marine traffic parsed by waterway and time of day.

 

Figure S14. Monthly distribution of 2019 marine traffic, parsed by time of day.

Figure S14. Monthly distribution of 2019 marine traffic, parsed by time of day.

 

Figure S15. Transit counts for 10 vessel types in 2019, displayed for each waterway in the study area separately.

Figure S15. Transit counts for 10 vessel types in 2019, displayed for each waterway in the study area separately.

 

Species distribution models

Table S10. Best-fitting density surface models for fin whales and humpback whales for mid-June – early-September.
Species Formula Trunc. dist. Family Link function Delta AIC Deviance explained
Fin whale (Lat x Lon) + seafloor depth + seafloor range 2.0 km Tweedie log 104 54%
Humpback whale (Lat x Lon x DOY) + seafloor depth + seafloor range + year 2.7 km Tweedie log 14 51%

 

Table S11. Fin whale density (bootstrapped 95% confidence interval) by waterway (whales per square km), , as estimated from the best-fitting density surface model.
Waterway Season
Caamano 0.022 (0-0.126)
Campania 0.024 (0-0.148)
Estevan 0 (0-0)
McKay 0 (0-0)
Squally 0.031 (0-0.169)
Verney 0 (0-0)
Whale 0 (0-0)
Wright 0 (0-0)
Study area 0.014 (0-0.118)
Table S12. Humpback whale density (bootstrapped 95% confidence interval) by waterway (whales per square km), , as estimated from the best-fitting density surface model.
Waterway Season June July August September
Caamano 0.059 (0.012-0.153) 0.119 (0.006-0.74) 0.057 (0.006-0.113) 0.046 (0.005-0.094) 0.049 (0.013-0.139)
Campania 0.07 (0.012-0.139) 0.056 (0.001-0.131) 0.063 (0.01-0.158) 0.071 (0.007-0.186) 0.097 (0.015-0.249)
Estevan 0.037 (0.004-0.071) 0.119 (0.006-0.153) 0.021 (0.001-0.024) 0.046 (0.006-0.121) 0.047 (0.008-0.107)
McKay 0.049 (0.003-0.112) 0.007 (0.001-0.036) 0.02 (0.001-0.04) 0.068 (0-0.134) 0.102 (0.017-0.313)
Squally 0.11 (0.025-0.251) 0.132 (0.021-0.429) 0.041 (0.002-0.099) 0.161 (0.037-0.448) 0.102 (0.01-0.2)
Verney 0.072 (0.006-0.282) 0.006 (0-0.035) 0.029 (0.001-0.108) 0.085 (0.006-0.231) 0.154 (0.004-0.786)
Whale 0.113 (0.023-0.298) 0.03 (0.003-0.111) 0.015 (0.002-0.048) 0.196 (0.026-0.502) 0.165 (0.034-0.512)
Wright 0.117 (0.007-0.308) 0.033 (0-0.139) 0.081 (0.01-0.204) 0.164 (0.034-0.566) 0.154 (0-0.425)
Study area 0.079 (0.01-0.223) 0.083 (0.001-0.417) 0.046 (0.002-0.125) 0.1 (0.007-0.359) 0.095 (0.01-0.32)

 

Seasonality

Table S13. Summary of GAM of seasonal fin whale abundance. This model was used to scale the June-September density estimate.
Family Formula edf P-value of coefficient Deviance explained
Negative binomial count ~ s(doy, k=5) + offset(log(minutes)) 2.803 7e-04 26%

 

Close-encounter rates

 

Table S14. Close encounter rate estimates for each species and vessel class used in this study. Here summertime and wintertime distributions are pooled.
Fin whales
Humpback whales
Vessel type Median Mean SD LCI UCI Median Mean SD LCI UCI FW - HW
Cargo > 180m 0.06 0.061 0.024 0.02 0.11 0.05 0.048 0.022 0.01 0.10 0.01
Cedar LNG tanker in-heel 0.08 0.086 0.030 0.04 0.15 0.07 0.070 0.025 0.03 0.12 0.01
Cedar LNG tanker in-product 0.08 0.086 0.031 0.03 0.14 0.07 0.067 0.025 0.03 0.12 0.01
Cedar LNG tug in-heel 0.02 0.024 0.015 0.00 0.06 0.01 0.016 0.013 0.00 0.04 0.01
Cedar LNG tug in-product 0.02 0.023 0.016 0.00 0.06 0.02 0.017 0.012 0.00 0.04 0.00
Fishing < 60m 0.02 0.023 0.015 0.00 0.05 0.01 0.015 0.012 0.00 0.04 0.01
LNG Canada tanker in-heel 0.09 0.087 0.026 0.04 0.14 0.07 0.071 0.025 0.03 0.12 0.02
LNG Canada tanker in-product 0.08 0.085 0.027 0.04 0.14 0.07 0.071 0.025 0.02 0.12 0.01
LNG Canada tug in-heel 0.02 0.024 0.014 0.00 0.06 0.02 0.016 0.012 0.00 0.04 0.00
LNG Canada tug in-product 0.02 0.022 0.015 0.00 0.05 0.01 0.015 0.012 0.00 0.04 0.01
Other < 40m 0.02 0.021 0.014 0.00 0.05 0.01 0.016 0.013 0.00 0.05 0.01
Other > 100m 0.04 0.046 0.021 0.01 0.09 0.04 0.038 0.021 0.01 0.09 0.00
Other > 40m 0.03 0.033 0.017 0.01 0.07 0.03 0.026 0.016 0.00 0.06 0.00
Passenger > 180m 0.06 0.061 0.023 0.02 0.11 0.05 0.051 0.020 0.01 0.10 0.01
Pleasurecraft < 40m 0.02 0.019 0.014 0.00 0.05 0.01 0.015 0.012 0.00 0.04 0.01
Sailing 0.02 0.019 0.013 0.00 0.05 0.01 0.014 0.012 0.00 0.04 0.01
Towing < 50m 0.02 0.024 0.015 0.00 0.05 0.02 0.020 0.014 0.00 0.05 0.00
Tug < 50m 0.02 0.024 0.015 0.00 0.06 0.02 0.019 0.014 0.00 0.05 0.00

 

Figure S16. Distributions of close-encounter rate estimates for each vessel type (row) and each whale species (color), based upon iterative simulations. Vertical lines indicate the median of each distribution. Here summertime and wintertime distributions are pooled.

Figure S16. Distributions of close-encounter rate estimates for each vessel type (row) and each whale species (color), based upon iterative simulations. Vertical lines indicate the median of each distribution. Here summertime and wintertime distributions are pooled.

 

Depth distribution

Table S15. Proportion of time fin whale spend above various depth cutoffs (1m, 2m, …, 30m), estimated for day and night separately based upon the mean and SD from six SPLASH-10 tag deployments.
Daytime
Nighttime
Depth (m) Mean SD Mean SD
1 8.7% 4.8% 8.3% 7.5%
2 14.4% 7.2% 18.1% 13.1%
5 26% 5.2% 41.1% 16.1%
10 37.1% 7.1% 59.2% 15.3%
15 47.5% 8% 72.1% 17%
20 55.4% 6.9% 82% 15.6%
25 60.9% 6.6% 85.3% 16%
30 63.3% 6.4% 89.5% 12.9%

 

Figure S17. Daytime (pink) and nighttime (teal) depth distribution curves for fin whale in and near the Kitimat Fjord System, representing the average proportion of time spent above a given depth across all tag deployments (n=6 in 2013 and 2014). Points on the left side of the plot represent the SD at each depth.

Figure S17. Daytime (pink) and nighttime (teal) depth distribution curves for fin whale in and near the Kitimat Fjord System, representing the average proportion of time spent above a given depth across all tag deployments (n=6 in 2013 and 2014). Points on the left side of the plot represent the SD at each depth.

 

Interaction rates

Table S16. Predictions of whale-vessel interaction rates for all vessel types in each traffic scheme.
Fin whales
Humpback whales
Traffic scheme Event Mean Median 95% CI 80% Conf. Mean Median 95% CI 80% Conf.
AIS 2019 Cooccurrence 509.21 509.0 471 - 549 488 5958.69 5961.0 5820 - 6099 5887.0
Close encounter 13.59 13.5 8 - 19 10 119.59 120.0 102 - 138 110.8
Strike-zone event 3.06 3.0 1 - 6 2 25.56 25.0 17 - 34 21.0
(1.5x draft) 3.00 3.0 0 - 6 2 25.59 25.0 18 - 34 21.0
AIS 2030 Cooccurrence 855.99 856.0 802 - 912 827 9428.00 9428.0 9222 - 9638 9322.8
Close encounter 22.79 22.5 16 - 31 19 184.71 184.0 164 - 209 173.0
Strike-zone event 4.89 5.0 2 - 9 3 39.13 39.0 29 - 50 34.0
(1.5x draft) 5.03 5.0 2 - 9 3 38.87 38.5 30 - 49 34.0
LNG Canada Cooccurrence 137.66 137.0 116 - 161 127 1710.28 1710.0 1637 - 1786 1670.0
Close encounter 7.20 7.0 3 - 12 5 70.41 70.0 57 - 85 63.0
Strike-zone event 3.01 3.0 0 - 6 1 30.11 30.0 22 - 39 25.0
(1.5x draft) 3.01 3.0 0 - 6 1 30.13 30.0 21 - 40 25.0
Cedar LNG Cooccurrence 19.40 19.0 13 - 27 16 236.57 237.0 211 - 262 223.0
Close encounter 1.06 1.0 0 - 3 0 9.75 10.0 5 - 15 7.0
Strike-zone event 0.44 0.0 0 - 2 0 4.37 4.0 1 - 8 3.0
(1.5x draft) 0.45 0.0 0 - 2 0 4.33 4.0 1 - 8 2.0
Total 2030 Cooccurrence 1013.05 1013.5 954 - 1074 981 11374.85 11373.0 11154 - 11590 11262.8
Close encounter 31.05 31.0 23 - 40 26 264.87 265.0 239 - 292 251.0
Strike-zone event 8.34 8.0 4 - 13 6 73.61 73.0 60 - 88 66.0
(1.5x draft) 8.50 8.0 4 - 14 6 73.33 73.0 59 - 87 66.0

 

 

Figure S18. Distribution of whale-vessel interaction rate predictions for AIS traffic in 2019.

Figure S18. Distribution of whale-vessel interaction rate predictions for AIS traffic in 2019.

 

Figure S19. Distribution of whale-vessel interaction rate predictions for AIS traffic in 2030.

Figure S19. Distribution of whale-vessel interaction rate predictions for AIS traffic in 2030.

 

Figure S20. Distribution of whale-vessel interaction rate predictions for LNG Canada traffic in 2030.

Figure S20. Distribution of whale-vessel interaction rate predictions for LNG Canada traffic in 2030.

 

Figure S21. Distribution of whale-vessel interaction rate predictions for Cedar LNG traffic in 2030.

Figure S21. Distribution of whale-vessel interaction rate predictions for Cedar LNG traffic in 2030.

 

Figure S22. Distribution of whale-vessel interaction rate predictions for all traffic in 2030 (AIS and LNG combined).

Figure S22. Distribution of whale-vessel interaction rate predictions for all traffic in 2030 (AIS and LNG combined).

 

 

Shares of interaction risk by vessel

 

Table S17. Share of interactions risk attributable to each vessel type, in 2019 and in 2030.
Fin whales
Humpback whales
Year Vessel Cooccurrence Close encounter Strike-zone event Cooccurrence Close encounter Strike-zone event
2019 Cargo > 180m 2 5 11 2 5 12
Fishing < 60m 13 11 6 16 12 7
Other < 40m 3 3 1 8 7 4
Other > 100m 3 5 7 7 13 20
Other > 40m 11 12 11 10 12 12
Passenger > 180m 7 17 27 3 8 13
Pleasurecraft < 40m 27 18 7 23 18 8
Sailing 11 8 3 10 6 3
Towing < 50m 14 12 16 9 9 11
Tug < 50m 10 8 11 11 10 11
2030 Cargo > 180m 2 4 6 2 4 7
Cedar LNG tanker in-heel 0 1 2 1 1 3
Cedar LNG tanker in-product 0 1 2 1 2 3
Cedar LNG tug in-heel 0 0 0 1 0 0
Cedar LNG tug in-product 0 0 0 1 0 0
Fishing < 60m 12 9 4 16 10 4
LNG Canada tanker in-heel 3 9 17 4 11 19
LNG Canada tanker in-product 3 9 15 4 11 18
LNG Canada tug in-heel 3 3 2 4 3 2
LNG Canada tug in-product 3 2 2 4 2 2
Other < 40m 0 0 0 0 0 0
Other > 100m 2 3 3 5 8 9
Other > 40m 7 7 6 7 7 6
Passenger > 180m 7 13 18 3 7 9
Pleasurecraft < 40m 24 15 4 22 15 5
Sailing 13 9 3 13 7 2
Towing < 50m 11 9 9 8 6 6
Tug < 50m 7 5 6 8 7 5

 

Figure S23. Share of interactions risk attributable to each vessel type, in 2019 and in 2030, for fin whales.

Figure S23. Share of interactions risk attributable to each vessel type, in 2019 and in 2030, for fin whales.

 

Figure S24. Share of interaction risk attributable to each vessel type, in 2019 and in 2030, for humpback whales.

Figure S24. Share of interaction risk attributable to each vessel type, in 2019 and in 2030, for humpback whales.

 

Shares of interaction risk by waterway

 

Table S18. Share of interactions risk attributable to each waterway, in 2019 and in 2030.
Fin whales
Humpback whales
Year Channel Cooccurrence Close encounter Strike-zone event Cooccurrence Close encounter Strike-zone event
2019 Caamano 61 60 63 14 14 17
Estevan 0 0 0 5 5 5
Campania 15 16 17 4 5 6
Squally 24 23 20 8 7 6
Whale 0 0 0 39 38 37
Wright 0 0 0 12 12 14
McKay 0 0 0 16 15 13
Verney 0 0 0 4 3 2
2030 Caamano 51 44 37 12 11 10
Estevan 0 0 0 6 7 8
Campania 13 12 10 4 4 3
Squally 35 43 52 11 13 16
Whale 1 1 1 43 46 49
Wright 0 0 0 9 8 7
McKay 0 0 0 12 10 6
Verney 0 0 0 3 2 1

 

Figure S25. Share of interaction risk attributable to each waterway, in 2019 and in 2030, for fin whales.

Figure S25. Share of interaction risk attributable to each waterway, in 2019 and in 2030, for fin whales.

 

Figure S26. Share of interactions risk attributable to each waterway, in 2019 and in 2030, for humpback whales.

Figure S26. Share of interactions risk attributable to each waterway, in 2019 and in 2030, for humpback whales.

 

Shares of interaction risk by month

 

Table S19. Share of interactions risk attributable to each month, in 2019 and in 2030.
Fin whales
Humpback whales
Year Month Cooccurrence Close encounter Strike-zone event Cooccurrence Close encounter Strike-zone event
2019 Jan 0 0 0 0 0 0
Feb 0 0 0 0 0 0
Mar 0 0 0 0 0 0
Apr 0 0 0 0 0 0
May 5 6 7 3 3 4
Jun 14 15 15 16 16 17
Jul 21 21 19 10 10 9
Aug 37 34 31 34 33 29
Sep 16 17 19 32 32 33
Oct 5 6 6 4 5 6
Nov 1 1 1 1 1 1
Dec 0 0 0 0 0 0
2030 Jan 0 0 0 0 0 0
Feb 0 0 0 0 0 0
Mar 0 0 0 0 0 0
Apr 0 1 1 0 0 0
May 5 5 7 3 3 3
Jun 14 15 15 16 16 16
Jul 21 21 22 11 11 11
Aug 37 33 27 37 36 35
Sep 16 17 20 28 28 28
Oct 6 6 7 4 5 6
Nov 1 1 1 1 1 1
Dec 0 0 0 0 0 0

 

Figure S27. Share of interactions risk attributable to each month, in 2019 and in 2030, for fin whales.

Figure S27. Share of interactions risk attributable to each month, in 2019 and in 2030, for fin whales.

 

Figure S28. Share of interactions risk attributable to each month, in 2019 and in 2030, for humpback whales.

Figure S28. Share of interactions risk attributable to each month, in 2019 and in 2030, for humpback whales.

 

Shares of interaction risk by diel period

 

Table S20. Share of interaction risk attributable to each diel period, in 2019 and in 2030.
Fin whales
Humpback whales
Year Diel period Cooccurrence Close encounter Strike-zone event Cooccurrence Close encounter Strike-zone event
2019 day 89 87 78 83 79 65
night 11 13 22 17 21 35
2030 day 87 84 71 82 78 64
night 13 16 29 18 22 36

 

Figure S29. Share of interactions risk attributable to each diel period, in 2019 and in 2030, for fin whales.

Figure S29. Share of interactions risk attributable to each diel period, in 2019 and in 2030, for fin whales.

 

Figure S30. Share of interactions risk attributable to each diel period, in 2019 and in 2030, for humpback whales.

Figure S30. Share of interactions risk attributable to each diel period, in 2019 and in 2030, for humpback whales.

 

Collisions & mortalities

 

Table S21. Predicted rates of collision and mortality for large ships (> 180m) in each traffic scheme and for each whale species.
Fin whales
Humpback whales
Traffic scheme Event Avoidance Mean Median 95% CI 80% Conf. Mean Median 95% CI 80% Conf.
AIS 2019 Collision 0.55 0.48 0 0 - 2 0 2.92 3 0 - 6 1
~ Speed 0.77 1 0 - 2 0 3.89 4 1 - 8 2
None 1.13 1 0 - 3 0 6.44 6 2 - 11 4
Mortality 0.55 0.47 0 0 - 2 0 2.73 3 0 - 6 1
~ Speed 0.74 1 0 - 2 0 3.70 4 1 - 7 2
None 1.08 1 0 - 3 0 6.06 6 2 - 10 4
AIS 2030 Collision 0.55 0.86 1 0 - 3 0 5.11 5 2 - 9 3
~ Speed 1.33 1 0 - 3 0 6.93 7 3 - 12 5
None 1.98 2 0 - 4 1 11.54 11 6 - 17 9
Mortality 0.55 0.82 1 0 - 2 0 4.78 5 2 - 9 3
~ Speed 1.29 1 0 - 3 0 6.55 6 3 - 11 4
None 1.90 2 0 - 4 1 10.80 11 6 - 17 8
LNG Canada Collision 0.55 1.24 1 0 - 3 0 12.39 12 7 - 19 9
~ Speed 1.18 1 0 - 3 0 11.69 11 6 - 18 9
None 2.71 3 0 - 6 1 27.46 27 19 - 37 23
Mortality 0.55 1.06 1 0 - 3 0 10.55 10 5 - 16 8
~ Speed 1.00 1 0 - 3 0 10.16 10 5 - 16 7
None 2.29 2 0 - 5 1 23.43 23 16 - 32 19
Cedar LNG Collision 0.55 0.17 0 0 - 1 0 1.74 2 0 - 4 1
~ Speed 0.17 0 0 - 1 0 1.56 1 0 - 4 0
None 0.41 0 0 - 2 0 3.92 4 1 - 8 2
Mortality 0.55 0.15 0 0 - 1 0 1.45 1 0 - 4 0
~ Speed 0.15 0 0 - 1 0 1.31 1 0 - 4 0
None 0.35 0 0 - 2 0 3.26 3 1 - 6 2
Total 2030 Collision 0.55 2.27 2 0 - 5 1 19.24 19 12 - 26 15
~ Speed 2.68 3 0 - 6 1 20.18 20 13 - 28 16
None 5.10 5 2 - 9 3 42.94 43 33 - 54 37
Mortality 0.55 2.03 2 0 - 4 1 16.78 17 10 - 24 13
~ Speed 2.44 2 0 - 5 1 18.02 18 12 - 25 14
None 4.54 4 1 - 8 3 37.48 37 28 - 48 32

 

Figure S31. Posterior distributions of collision and mortality estimates for fin whales (a - b) and humpback whales (c-d), for each traffic scheme we analyzed.

Figure S31. Posterior distributions of collision and mortality estimates for fin whales (a - b) and humpback whales (c-d), for each traffic scheme we analyzed.

 

 

Figure S32. Share of collision and mortality risk attributable to each vessel type, in 2019 and in 2030.

Figure S32. Share of collision and mortality risk attributable to each vessel type, in 2019 and in 2030.

 

Table S22. Share of large ship (>180m) collision and mortality risk attributable to each waterway, in 2019 and in 2030.
Fin whales
Humpback whales
Collision
Mortality
Collision
Mortality
Waterway 2019 2030 2019 2030 2019 2030 2019 2030
Caamano 59 29 61 30 17 9 17 10
Estevan 0 0 0 0 5 8 4 8
Campania 25 11 23 13 7 4 7 4
Squally 15 59 15 56 5 16 5 16
Whale 0 1 1 1 39 50 39 50
Wright 0 0 0 0 14 7 15 7
McKay 0 0 0 0 12 5 12 5
Verney 0 0 0 0 1 0 1 0

 

Figure S33. Share of collision and mortality risk attributable to each waterway, in 2019 and in 2030.

Figure S33. Share of collision and mortality risk attributable to each waterway, in 2019 and in 2030.

 

Table S23. Share of large ship (>180m) collision and mortality risk attributable to each month, in 2019 and in 2030.
Fin whales
Humpback whales
Collision
Mortality
Collision
Mortality
Month 2019 2030 2019 2030 2019 2030 2019 2030
1 0 0 0 0 0 0 0 0
2 0 0 0 0 0 0 0 0
3 0 0 0 0 0 0 0 0
4 0 1 1 1 0 1 0 1
5 4 5 5 5 3 3 3 3
6 21 18 23 18 17 16 17 17
7 19 21 16 19 11 11 11 11
8 30 27 27 29 30 36 30 35
9 21 19 23 21 32 27 32 27
10 3 7 3 7 5 5 5 5
11 0 1 1 1 1 1 1 1
12 0 0 0 0 0 0 0 0

 

Figure S34. Share of collision and mortality risk attributable to each month, in 2019 and in 2030.

Figure S34. Share of collision and mortality risk attributable to each month, in 2019 and in 2030.

 

Table S24. Share of large ship (>180m) collision and mortality risk attributable to each diel period, in 2019 and in 2030.
Fin whales
Humpback whales
Collision
Mortality
Collision
Mortality
Diel period 2019 2030 2019 2030 2019 2030 2019 2030
day 80 73 83 72 61 61 60 62
night 20 27 17 28 39 39 40 38

 

Figure S35. Share of collision and mortality risk attributable to each diel period, in 2019 and in 2030.

Figure S35. Share of collision and mortality risk attributable to each diel period, in 2019 and in 2030.

 

Chances of certain outcome severities

 

Table S25. Chances of various large ship (>180m) impact severities for fin whales and humpback whales, due to present-day AIS-transmitting traffic (represented by 2019 traffic), projected AIS-transmitting traffic in 2030, projected LNG Canada traffic, projected Cedar LNG traffic, then all traffic in 2030 (previous categories combined).
AIS 2019
AIS 2030
LNG Canada
Cedar LNG
All traffic 2030
Species Chances (%) of… Coll. Mort. Coll. Mort. Coll. Mort. Coll. Mort. Coll. Mort.
Fin whale Zero 33.1 37.7 14.0 19.1 28.5 33.7 83.4 85.6 3.8 6.0
At least 1 66.9 62.3 86.0 80.9 71.5 66.3 16.6 14.4 96.2 94.0
At least 2 32.9 26.6 55.0 45.8 34.8 27.1 1.3 0.9 83.7 76.0
At least 3 11.1 7.5 27.1 20.9 13.8 9.3 0.0 0.0 65.2 52.8
At least 4 3.4 1.6 11.7 8.5 4.8 2.1 0.0 0.0 41.9 30.9
At least 5 0.6 0.2 5.2 2.6 0.9 0.4 0.0 0.0 24.2 16.5
Humpback whale Zero 0.0 0.3 0.0 0.0 0.0 0.0 18.7 25.4 0.0 0.0
At least 1 100.0 99.7 100.0 100.0 100.0 100.0 81.3 74.6 100.0 100.0
At least 2 99.8 99.4 100.0 100.0 100.0 100.0 49.4 38.3 100.0 100.0
At least 3 99.1 97.9 100.0 100.0 100.0 99.8 24.3 18.1 100.0 100.0
At least 4 97.8 96.1 100.0 99.8 99.9 99.6 9.7 6.2 100.0 100.0
At least 5 95.6 89.8 99.9 99.4 99.5 98.6 3.0 1.3 100.0 100.0

 

Table S26. Chances of large ship (>180m) impact severities for fin whales and humpback whales, similar to above, now described as the chances of experiencing no more than the stated number of events.
AIS 2019
AIS 2030
Cedar LNG
LNG Canada
All traffic 2030
Species Chances (%) of… Coll. Mort. Coll. Mort. Coll. Mort. Coll. Mort. Coll. Mort.
Fin whale Zero 33.1 37.7 14.0 19.1 83.4 85.6 28.5 33.7 3.8 6.0
Max of 1 67.1 73.4 45.0 54.2 98.7 99.1 65.2 72.9 16.3 24.0
Max of 2 88.9 92.5 72.9 79.1 100.0 100.0 86.2 90.7 34.8 47.2
Max of 3 96.6 98.4 88.3 91.5 100.0 100.0 95.2 97.9 58.1 69.1
Max of 4 99.4 99.8 94.8 97.4 100.0 100.0 99.1 99.6 75.8 83.5
Max of 5 99.7 99.8 98.3 99.3 100.0 100.0 99.6 99.8 87.6 93.1
Humpback whale Zero 0.0 0.3 0.0 0.0 18.7 25.4 0.0 0.0 0.0 0.0
Max of 1 0.2 0.6 0.0 0.0 50.6 61.7 0.0 0.0 0.0 0.0
Max of 2 0.9 2.1 0.0 0.0 75.7 81.9 0.0 0.2 0.0 0.0
Max of 3 2.2 3.9 0.0 0.2 90.3 93.8 0.1 0.4 0.0 0.0
Max of 4 4.4 10.2 0.1 0.6 97.0 98.7 0.5 1.4 0.0 0.0
Max of 5 9.9 20.7 0.5 1.7 99.2 99.8 1.2 4.3 0.0 0.0

 

Validation

 

Fin whales

## Melting outcomes & prepping the posterior ...
## Determining the probability of your observations ...
## Likelihood of your observation, assuming perfect detection = 0.002
## Finding the strike detection rate (SDR) that would make your observations plausible ...
## preparing L ~ SDR plot ...
## --- SDR needed for P(Observation) of 0.05 = 0.5
## --- SDR needed for P(Observation) of 0.10 = 0.39
## --- SDR needed for P(Observation) of 0.20 = 0.245
## --- SDR needed for P(Observation) of 0.55 = 0.095
Figure S36. Results of ship-strike model validation for fin whales, in which the likelihood of not observing a strike in the last decade was estimated according to our model results. Left: Distribution of strike observations predicted with our models when assuming perfect detection (i.e., no strikes missed). The red dashed line indicates what we actually observed. Right: The probability of our observations under various scenarios of imperfect detection. Dashed lines indicate conventional alpha levels of significance.

Figure S36. Results of ship-strike model validation for fin whales, in which the likelihood of not observing a strike in the last decade was estimated according to our model results. Left: Distribution of strike observations predicted with our models when assuming perfect detection (i.e., no strikes missed). The red dashed line indicates what we actually observed. Right: The probability of our observations under various scenarios of imperfect detection. Dashed lines indicate conventional alpha levels of significance.

 

Humpback whales

## Melting outcomes & prepping the posterior ...
## Determining the probability of your observations ...
## Likelihood of your observation, assuming perfect detection = 0
## Finding the strike detection rate (SDR) that would make your observations plausible ...
## preparing L ~ SDR plot ...
## --- SDR needed for P(Observation) of 0.05 = 0.16
## --- SDR needed for P(Observation) of 0.10 = 0.13
## --- SDR needed for P(Observation) of 0.20 = 0.09
## --- SDR needed for P(Observation) of 0.55 = 0.035
Fig S37. Results of ship-strike model validation for humpback whales, in which the likelihood of not observing a strike in the last decade was estimated according to our model results. Left: Distribution of strike observations predicted with our models when assuming perfect detection (i.e., no strikes missed). The red dashed line indicates what we actually observed. Right: The probability of our observations under various scenarios of imperfect detection. Dashed lines indicate conventional alpha levels of significance.

Fig S37. Results of ship-strike model validation for humpback whales, in which the likelihood of not observing a strike in the last decade was estimated according to our model results. Left: Distribution of strike observations predicted with our models when assuming perfect detection (i.e., no strikes missed). The red dashed line indicates what we actually observed. Right: The probability of our observations under various scenarios of imperfect detection. Dashed lines indicate conventional alpha levels of significance.

Mitigation measures

Scenarios 3 (rescheduling) & 4 (moratoria)

Figure S38. Efficacy of mitigation categories 3 (LNG rescheduling) and 4 (LNG moratoria) for fin whales, when those measures are applied to different months of the year for various durations (one - three months).

Figure S38. Efficacy of mitigation categories 3 (LNG rescheduling) and 4 (LNG moratoria) for fin whales, when those measures are applied to different months of the year for various durations (one - three months).

Figure S39. Efficacy of mitigation categories 3 (LNG rescheduling) and 4 (LNG moratoria) for humpback whales, when those measures are applied to different months of the year for various durations (one - three months).

Figure S39. Efficacy of mitigation categories 3 (LNG rescheduling) and 4 (LNG moratoria) for humpback whales, when those measures are applied to different months of the year for various durations (one - three months).

Discussion

Density estimate comparison throughout region

  # Fin whales (Gitga'at average)
  0.014 / 0.007 # eez (Wright)
## [1] 2
  0.014 / 0.002 # north coast (Wright)
## [1] 7
  0.014 / 0.003 # vancouver island (Nichol)
## [1] 4.666667

  # Fin whales (Squally Ch)
  0.031 / 0.007 # eez
## [1] 4.428571
  0.031 / 0.002 # north coast
## [1] 15.5
  0.031 / 0.003
## [1] 10.33333

  # Humpback whales (Gitga'at average)
  0.079 / 0.016 # eez (Wright)
## [1] 4.9375
  0.079 / 0.025 # north coast (Wright)
## [1] 3.16
  0.079 / 0.014 # vancouver island (Nichol)
## [1] 5.642857

  # Humpback whales (Wright Sound)
  0.0117 / 0.016 # eez
## [1] 0.73125
  0.0117 / 0.025 # north coast
## [1] 0.468
  0.0117 / 0.014
## [1] 0.8357143